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Seasonal trends in depressive problems among United States children and adolescents: A representative population survey
Psychiatry Research 170 (2009) 224–228
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Psychiatry Research j o u r n a l h o m e p a g e : w w w. e l s ev i e r. c o m / l o c a t e / p s yc h r e s
Seasonal trends in depressive problems among United States children and adolescents: A representative population survey Yael I. Nillni a, Kelly J. Rohan a,⁎, David Rettew b, Thomas M. Achenbach b a b
Department of Psychology, University of Vermont, John Dewey Hall, 2 Colchester Ave., Burlington, VT, USA Department of Psychiatry, University of Vermont, 1 South Prospect St., Burlington, VT, USA
a r t i c l e
i n f o
Article history: Received 30 April 2008 Received in revised form 10 July 2008 Accepted 22 July 2008 Keywords: Seasonal affective disorder Depression Epidemiology
a b s t r a c t This study examined season-of-assessment differences in parent and child reports of depressive problems on well-validated instruments in 2009 U.S. children and adolescents, aged 6 to 18 years, from a nationally representative population survey. A parent completed the Child Behavior Checklist (CBCL) for each participant and 1226 of the 11–18-year-olds completed the Youth Self-Report (YSR). Outcome measures were CBCL and YSR withdrawn/depressed syndrome scale scores and rates of clinically elevated scores. Overall fall/ winter versus spring/summer differences were not found on the CBCL or YSR for depressive problem severity or rates of depressive problems. Age, sex, and latitude were examined as potential moderators of the association between season-of-assessment and the outcomes. Of these, the effect of season-of-assessment on CBCL depressive problem severity depended upon age. Parents of 16–18-year-old adolescents rated depressive problems as significantly more severe in fall and winter than in spring and summer. Parents also rated depressive problems as significantly more severe in 16–18-year-olds than in 6–15-year-olds, but only when assessed in the fall and winter. There were no season-of-assessment differences among 6–15-year-old children and adolescents. The overall lack of season-of-assessment differences and the finding of age as a moderator on only one of four outcomes suggest minimal seasonality effects. © 2008 Elsevier Ireland Ltd. All rights reserved.
1. Introduction The essential feature of Major Depressive Disorder, Recurrent with a Seasonal Pattern is the onset and remission of major depressive episodes at predictable times during the year (American Psychiatric Association, 2000). The most common seasonal pattern is winter seasonal affective disorder (SAD), characterized by depressive episodes that begin in the fall or winter and remit in the spring. Reported prevalence rates for SAD in adults vary considerably, ranging from less than 1% to 9.7% across many countries (Magnusson, 2000, 2005). In contrast to the numerous adult studies, there is considerably less epidemiological research on SAD among children and adolescents. Retrospectively reported prevalence of seasonal onset of depressive symptoms has ranged from 3.3% to 4.2% among American youths (Carskadon and Acebo, 1993; Swedo et al., 1995). Carskadon and Acebo (1993) asked parents of 1860 9- to 12-year-old American children to retrospectively report on their child's seasonal changes in sleeping, eating, irritability, energy, withdrawal, and sadness in the fall (September–November), winter (December–February), and spring (March–May) over the preceding 2 years. A substantial minority (48.5%) of the parents reported at least one recurring symptom in the winter, and 4.2% reported “seems
⁎ Corresponding author: Tel.: +1 802 656 0798; fax: +1 802 656 8783. E-mail address: [email protected] (K.J. Rohan). 0165-1781/$ – see front matter © 2008 Elsevier Ireland Ltd. All rights reserved. doi:10.1016/j.psychres.2008.07.011
sad” plus two other winter symptoms, suggesting that at least subclinical forms of SAD (i.e., the “winter blues”) may be relatively common. In a suburban Maryland sample of 1835 9- to 19-year-olds, 3.3% met criteria for SAD when they completed a modified version of the Seasonal Pattern Assessment Questionnaire (SPAQ; Rosenthal et al., 1987) in late September and early October (Swedo et al., 1995). In contrast, population surveys of Washington, D.C. metro area adults found SPAQprevalence of SAD ranging from 4.3% to 6.3% (Kasper et al., 1989; Rosen et al.,1990). An epidemiological survey of over 1400 Finnish seventh and ninth graders found that 60% to 90% reported seasonal variations in mood and behavior on a modified version of the SPAQ completed during the last week of March (Sourander et al., 1999). A recent study of 1709 Italian children and adolescents who ranged in age from 10 to 17 years found an 8.6% SPAQ-assessed prevalence of SAD (Tonetti et al., 2007). In the Swedo et al. (1995), Sourander et al. (1999), and Tonetti et al. (2007) studies, the SPAQ was modified to include pediatric symptoms of SAD such as poor school performance, conduct problems, and irritability. In conclusion, limited data suggest that fall/winter depression may exist in children and adolescents at rates slightly lower than those reported for adults. As a limitation, most findings were obtained with a modified version of the SPAQ, which, though valuable as a screening tool, may lack specificity and sensitivity (Magnusson, 1996). SPAQderived criteria have been shown to overestimate the prevalence of SAD compared with a diagnostic interview based on DSM-IV criteria (Levitt and Boyle, 2002). The National Comorbidity Study reported prevalence
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rates of 0.4% for major depression with a seasonal pattern and 1% for minor depression with a seasonal pattern, based on DSM-III and DSM-IV criteria in a random US community sample of 8098 adolescents and adults, aged 15–54 (Blazer et al., 1998). Furthermore, the SPAQ is a retrospective survey that was not designed or standardized for pediatric samples. Assessment during either spring or fall poses the potential problem of poor recall for actual symptoms experienced during prior winter seasons. In support of this possibility, SPAQ global seasonality scores and responses to the SPAQ question of whether or not seasonal changes constitute a problem (both of which are considered in the SPAQ diagnosis of SAD) are not associated with prospectively measured summer–winter differences in mood (Murray, 2003). Previous research is also limited by the restricted age range of the samples studied. To our knowledge, there are no published data on SAD in children under the age of 9. Importantly, none of the previous reports on SAD among U.S. children and adolescents used a nationally representative sample, and prior studies included either child or parent reports, but not both. Thus, research on representative samples assessed with well-validated pediatric instruments from the perspective of both child and parent is needed to shed light on possible seasonal variations in mood among children and adolescents. Increased understanding is also needed regarding potential moderators of seasonal trends. Several studies have shown a significant association between latitude and SAD prevalence among adults in the United States, whereby the prevalence of SAD is higher at northern than at southern latitudes (Rosen et al., 1990; Mersch et al., 1999; Magnusson, 2005). However, these studies are limited by their exclusive use of the SPAQ. The National Comorbidity Survey did not find a latitude effect when using DSM-III and DSM-IV criteria for SAD diagnosis (Blazer et al., 1998). Furthermore, the prevalence of DSM-IV SAD diagnoses did not differ by latitude among 1605 participants throughout Canada (41.5°N to 49.5°N; Levitt and Boyle, 2002). Only two studies have examined the relation between latitude and SAD among children and adolescents. Consistent with the SPAQ-based adult literature, both studies reported greater seasonality at higher latitudes (Carskadon and Acebo, 1993; Sourander et al., 1999), but one study found this only for girls (Sourander et al., 1999). The Swedo et al. (1995) survey found that age correlated positively with SAD prevalence. For females only, participants who were postpubescent (determined by whether they had begun menarche) had a higher prevalence of SAD (4.5%) than females who were pre-pubescent (1.7%). Similarly, the Tonetti et al. (2007) survey found that, regardless of gender, seasonality scores increased with age; however, beginning at age 14, females displayed higher seasonality scores than males (Tonetti et al., 2007). This parallels findings of higher rates of non-seasonal depression for females than males after puberty (Hankin et al., 1998). Using a national sample of 6- to 18-year-olds selected to be representative of U.S. demographics on ethnicity, socioeconomic status, and geographic location, we had the following aims: (1) to compare depressive problem severity and clinical levels of depressive problems among children and adolescents assessed in the fall and winter (September–February) versus the spring and summer (March–August), and (2) to test whether age, gender, and latitude would moderate associations between season-of-assessment and depressive problem severity and prevalence. We hypothesized that (1) depressive problem severity and the prevalence of clinical levels of depressive problems would be greater in the fall and winter versus the spring and summer. Based on prior reports that seasonality of mood correlated positively with age (Swedo et al., 1995; Tonetti et al., 2007), we hypothesized that (2) older participants would have greater depressive problem severity and prevalence in the fall and winter than younger participants. In addition, based on prior studies (Swedo et al., 1995; Tonetti et al., 2007), we hypothesized that (3) the main effects of age and gender would interact, whereby fall/winter depressive problem severity and prevalence would be higher for females than males but only among older adolescents. Lastly, based on two preliminary reports (Carskadon and
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Acebo, 1993; Sourander et al., 1999), we hypothesized that (4) fall/ winter depressive problems would be more severe and prevalent for individuals in northern than in southern latitudes. 2. Methods 2.1. Participants and procedure Participants were assessed in a national survey conducted from February 1999 through January 2000 (Achenbach and Rescorla, 2001), using a national sampling frame maintained by Temple University's Institute for Survey Research (ISR) that insured a nationally representative sample across ethnicity, socioeconomic status, and geographic location. Approximately 150 households in each of 100 Primary Sampling Units (PSUs; i.e., areas that are collectively representative of the 48 contiguous United States) were visited in order to determine eligibility for the study. Eligible residents for the current study were at least 6 years old and had no major physical problems or mental retardation. They were selected by stratified randomized procedures that yielded similar proportions of each gender at each age. One parent of each eligible, randomly chosen 6- to 18-year-old participated. During an in-home interview, parents completed the Child Behavior Checklist (CBCL) and answered demographic questions. Youths aged 11 to 18 years were asked to complete the Youth Self-Report (YSR). Of the 2181 eligible 6- to 18-year-olds, parents of 2009 (92.1%) completed the CBCLs that were used in this study. The sample (N = 2009) included participants from 40 states and the District of Columbia. Table 1 summarizes demographics. Of the 1285 eligible 11- to 18-year-olds, 1226 (95.4%) completed the YSR and were included in analyses of youth-rated depressive problems. 2.2. Measures The Child Behavior Checklist (CBCL; Achenbach and Rescorla, 2001) is a widely used instrument that assesses a broad range of competencies and problems. The reliability and validity of the CBCL are well established (Achenbach and Rescorla, 2001). It includes 120 specific problem items and 20 competence items in areas such as social and school functioning. The parent rates problem items over the past 6 months as 0 = “not true (as far as you know),” 1 = “somewhat or sometimes true,” and 2 = “very true or often true.” These problem items are scored on statistically derived syndrome scales and on DSM-oriented scales. Because the CBCL does not have a specific SAD scale, we examined the items of several scales to identify the scale with the best conceptual fit to SAD. The DSM Affective Problems Scale, the anxious/depressed syndrome scale, and the withdrawn/depressed syndrome scale were all considered. We also constructed our own SAD scale using items that tapped the following problems: “overeating,” “sleeps more,” “feels worthless,” “enjoys little,” “would rather be alone,” “lacks energy,” “sad,” “withdrawn,” “guilty,” “overtired,” and “irritable.” The 10-item Affective Problems scale, although consistent with DSM-IV criteria for Major Depression, contains two suicide items (i.e., harms self and talks about suicide) that might be confounded with the widely replicated spring peak in suicides (Doganay et al., 2003; Lee et al., 2006). The anxious/depressed scale contains many anxiety symptoms not common in SAD. We, therefore, focused on the new SAD scale and on the withdrawn/depressed syndrome scale, which, of the empirically derived scales, includes items most representative of SAD symptoms (“enjoys little,” “would rather be alone,” “won’t talk,” “secretive,” “shy/timid,” “lacks energy,” “sad,” and “withdrawn”). The withdrawn/depressed scale is scored by summing the ratings on its constituent items. In addition, there are dichotomous cutoff points reflecting “clinical” and “borderline clinical” levels of problems based on the distribution of scale scores. Depressive problem severity was measured by continuous raw scores on the withdrawn/ depressed scale, which can range from 0 to 16. Continuous raw scores on the new SAD scale were used as a secondary measure of depressive problem severity. Clinical levels of depressive problems were defined as withdrawn/depressed scores in the combined borderline and clinical ranges, i.e., ≥ 93rd percentile for the child's age and gender, based on the CBCL normative samples. We did not examine clinically elevated levels of scores on the SAD scale because there is no empirically defined clinical cut point.
Table 1 Demographic information for 6- to 18-year-olds with parent ratings on the Child Behavior Checklist (N = 2009). Age, M (S.D.) Gender, No. (%) Male Female Ethnicity, No. (%) White African American Asian American Indian/Alaska Native Hispanic/Latino Pacific Islander Socioeconomic Status, M (S.D.)a
12.0 (0.5) 1073 (52.8%) 956 (47.1%) 1241 (61.1%) 387 (19.1%) 165 (8.1%) 18 (0.9%) 179 (8.8%) 39 (1.9%) 5.5 (1.9)
a Based on Hollingshead's (1975) 9-step scale for the parent having the higher status occupation.
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The Youth Self-Report (YSR; Achenbach and Rescorla, 2001) is a companion instrument of the CBCL designed to be completed by youths aged 11–18. The reliability and validity of the YSR are well established (Achenbach and Rescorla, 2001). Measures included YSR withdrawn/depressed syndrome scale raw scores and clinical status (≥93rd percentile based on norms). Continuous raw scores on the newly created YSR SAD scale represented a secondary measure of depressive problem severity. Latitude of the child's residence was assigned to one of five categories ≥45°N, 40°– 44°N, 35°–39°N, 30°–34°N, and 25°–29°N. Socioeconomic status (SES) was scored on Hollingshead's (1975, unpublished manuscript) 9-step scale for the parent having the higher status occupation. 2.3. Data analysis SPSS 12.0 was used for all analyses with alpha b 0.05, 2-tailed. The outcome measures were depressive problem severity and point-prevalence for elevated depressive problems scores in the combined clinical and borderline clinical range. A one-way analysis of variance tested differences in withdrawn/depressed scores on the CBCL and YSR between questionnaires completed in the fall/winter versus those completed in the spring/summer. This dichotomous categorization of season was chosen to avoid the very unequal sample sizes in a comparison of all four seasons (fall: Sep.–Nov. = 708, winter: Dec.–Feb.= 272, spring: March–May= 1009, and summer: Jun.–Aug. =20), which would have violated the ANOVA assumption that sample sizes should be nearly equal (Ott, 1993). When we combined fall with winter, the sample size was 980 for the CBCL and 612 for the YSR, while for spring combined with summer, the sample size was 1029 for the CBCL and 614 for the YSR. The ANOVA was repeated using the new SAD scale on both measures. The proportions of children and adolescents meeting borderline or clinical levels of depressive problems on the CBCL and YSR withdrawn/depressed scales within fall/winter and spring/summer were compared using Chi-square. The second set of analyses tested whether age, gender, and/or latitude moderated the relation between season-of-assessment and depressive problem severity. To examine age, gender, their combined influence, and latitude an ANCOVA tested the main effects of age, gender, season, and latitude as well as the 2-way and 3-way interactions between these main effects, while controlling for the main effects of ethnicity and SES as covariates. ANCOVAs were applied to the CBCL and YSR withdrawn/depressed scale scores and to the new SAD scale on both measures. A hierarchical logistic regression tested whether age, gender, latitude and the interaction of age and gender moderate the relation between season-of-assessment and clinical levels of depressive problems. Age, gender, SES, ethnicity, and latitude were entered in step 1; season-of-assessment (fall/winter versus spring/summer) was entered in step 2; the interaction term for age × gender was entered in step 3; and the interaction terms for gender × season, age × season, season × age × gender, and season× latitude were entered in step 4. The above analyses were repeated using the YSR withdrawn/depressed dichotomous outcome variable of borderline clinical or higher levels of depressive problems as the dependent measure. In order to reduce multicollinearity and maximize interpretability, the predictors used in each interaction were mean centered prior to running the analysis using the procedures outlined by Aiken and West (1991).
3. Results 3.1. Correlations between child and parent reports Tables 2 and 3 summarize the correlations between child and parent reports. All combinations of parent scores versus child yielded low to moderate correlations. This is consistent with previous findings on correlations between parent and self-reports (Achenbach et al., 1987). 3.2. Seasonal trends in depressive problem severity and prevalence— Hypothesis 1 Because results on the SAD scale replicated those on the empirically validated depressed/withdrawn syndrome scales, we present results Table 2 Pearson correlations between parent-completed CBCL withdrawn/depressed raw score and child-completed YSR withdrawn/depressed raw score.
All parents Mother Father Other guardian ⁎⁎P b 0.01 (2-tailed). ⁎P b 0.05 (2-tailed).
All children
Female child
Male child
r (n)
r (n)
r (n)
0.36 (1235)⁎⁎ 0.36 (887)⁎⁎ 0.33 (261)⁎⁎ 0.45 (87)⁎⁎
0.42 (585)⁎⁎ 0.44 (428)⁎⁎ 0.31 (113)⁎⁎ 0.52 (44)⁎⁎
0.31 (650)⁎⁎ 0.30 (459)⁎⁎ 0.35 (148)⁎⁎ 0.32 (43)⁎
Table 3 Pearson correlations between clinically elevated scores of the withdrawn/depressed scale on the parent-completed CBCL and child-completed YSR.
All parents Mother Father Other guardian
All children
Female child
Male child
r (n)
r (n)
r (n)
0.24 (1235)⁎⁎ 0.26 (887)⁎⁎ 0.19 (261)⁎⁎
0.30 (585)⁎⁎ 0.33 (428)⁎ 0.18 (113) 0.30 (44)
0.20 (650)⁎⁎ 0.21 (459)⁎⁎ 0.20 (148)⁎ 0.10 (43)
0.20 (87)
⁎⁎P b 0.01 (2-tailed). ⁎P b 0.05 (2-tailed).
only for the withdrawn/depressed scale. The one-way ANOVAs and Chi squares yielded no significant fall/winter versus spring/summer differences in depressive problem severity [F1, 2007 = 0.92; P = 0.34, η2 = 0.000] or prevalence [χ21 = 1.089; P = 0.297, Φ = 0.023] on the CBCL withdrawn/depressed scale or on the YSR withdrawn/depressed scale [F1, 1225 = 1.46; P = 0.23, η2 = 0.001 and χ21 = 0.622; P = 0.430, Φ = 0.023]. Table 4 presents fall/winter and spring/summer raw scores and rates of clinically elevated scores on the CBCL and YSR. 3.3. Age and sex as moderators of the relation between season-ofassessment and depressive problem severity and prevalence—Hypotheses 2 and 3 In both the ANCOVA and logistic hierarchical regression analyses, the gender × season-of-assessment interaction was not significant for either the CBCL or YSR. The age × season-of-assessment interaction term was significant for depressive problem severity on the CBCL, F1, 1898 = 5.2; P = 0.023, η2 = 0.003 in the ANCOVA, suggesting that the effect of age depends upon season-of-assessment, while controlling for gender, ethnicity, SES, latitude, and the main effects of age and season. In order to explore this interaction further, we performed post-hoc ANCOVAs to test the effect of season at each age on depressive symptom severity, while controlling for gender, ethnicity, SES, and latitude. The adjusted means of depressive problem severity at each age and season are shown in Fig. 1. Although there were no significant season-ofassessment differences when each age was examined separately, we observed a consistent pattern of fall/winter elevation of depressive problem severity over spring/summer depressive problems beginning at age 16. We re-ran the ANCOVA, using age categories (6–15 and 16–18) in order to compare these two age groups. The age category× season-ofassessment interaction term was significant for depressive problem severity on the CBCL, F1, 1898 = 8.4; P = 0.004, η2 = 0.004 (Fig. 2). Posthoc analyses revealed that depressive problem severity scores were significantly higher in the fall/winter than in the spring/summer among older adolescents, aged 16–18, F1, 383 = 4.6; P = 0.032, η2 = 0.012, but did not differ across season-of-assessment among younger children and adolescents, aged 6–15, F1, 1511 = 2.3; P = 0.132, η2 = 0.001. The effect size corresponding to the season-of-assessment difference among
Table 4 Mean withdrawn/depressed scores and rates of clinically elevated scores in fall/winter and spring/summer seasons of assessment. Season-of-assessment Measure
Fall/winter
Spring/summer
Raw scores, M (S.D.), n CBCL w/d YSR w/d
1.5 (2.2), 980 3.0 (2.6), 612
1.8 (2.2), 1029 3.2 (2.6), 614
Rates of clinically elevated scores, No. (%) CBCL w/d 86 (9.6%) YSR w/d 50 (8.2%)
100 (9.0%) 58 (9.5%)
CBCL w/d = Child Behavior Checklist withdrawn/depressed syndrome scale, YSR w/ d = Youth Self-Report withdrawn/depressed syndrome scale. Rate of clinically elevated scores is defined as scores ≥ 93rd percentile based on CBCL and YSR normative samples.
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3.4. Latitude as a moderator of the relation between season-of-assessment and depressive problem severity and prevalence—Hypothesis 4 The latitude × season-of-assessment interaction was not significant in either the ANCOVA analysis or the logistic regressions, suggesting that latitude did not significantly moderate the relation between season-of-assessment and depressive problem severity and prevalence on either the CBCL or the YSR. 4. Discussion
Fig. 1. Mean CBCL withdrawn/depressed syndrome scale scores in fall/winter versus spring/summer for participants aged 6–18, adjusted for gender, ethnicity, SES, and latitude.
16 to 18-year-olds was d = 0.15. Age category differences were then examined separately for each season. Parents of adolescents aged 16–18 reported significantly more depressive problems than parents of children and adolescents aged 6–15 when assessed in the fall and winter, F1, 925 = 26.98; P = 0.000, η2 = 0.028. The effect size corresponding to the age category group difference (6–15 versus 16–18) within the fall/winter season-of-assessment was d = 0.24. There were no differences between these two age groups on CBCL depressive problem severity when assessed in the spring and summer, F1, 969 = 1.5; P = 0.227, η2 = 0.002. The age × season-of-assessment interaction was not significant in the ANCOVA for YSR scores or in the hierarchical logistic regressions of combined borderline and clinical levels of depressive problems according to the CBCL and YSR. The 3-way age × gender × season interaction was not significant on the CBCL or YSR in the ANCOVA analysis using raw scores or in the logistic regressions using borderline or clinical status. Given that the age × season-of-assessment interaction was significant for CBCL scores, but not for YSR scores, we examined whether differences in parent–child agreement might explain this discrepancy. As only 11–18-year-olds completed the YSR, we examined correlations between parent reports on the CBCL and child reports on the YSR separately for ages 11–15 versus 16–18. Correlations between parent and child reports of depressive problem severity did not differ by age subsample (r = 0.34 for 11–15 versus r = 0.38 for 16–18; z = −0.75, P = 0.45). Therefore, it does not appear likely that a difference in parent–child agreement explains these discrepant findings.
Fig. 2. Mean CBCL withdrawn/depressed syndrome scale scores in fall/winter versus spring/summer for participants aged 6–14 and 15–18, adjusted for gender, ethnicity, SES, and latitude.
To our knowledge, this is the first study to examine seasonal trends in depressive problem severity and prevalence in a sample representative of U.S. children and adolescents across ethnicity, SES, and geographic location. It is also the first to use a validated pediatric measure of depressive problem severity and borderline or clinical status of these depressive problems to test season-of-assessment differences as well as gender, age, and latitude as potential moderators. This study also included the widest age span to date, ages 6 to 18 years. In the sample as a whole, depressive problem severity and prevalence did not differ according to whether problems were reported in the fall and winter versus in the spring and summer (Hypothesis 1 was not supported). However, age was found to significantly moderate the relation between season-of-assessment and depressive problem severity on the CBCL (Hypothesis 2 was supported on one of four outcome measures). Specifically, parents of older adolescents (aged 16–18) rated their adolescents' depressive problems as significantly more severe in the fall or winter than in the spring or summer. Younger children and adolescents (aged 6–15) showed no significant season-of-assessment differences in depressive problem severity. When assessed in the fall and winter, 16- to 18-year-olds had significantly greater depressive problems, as rated by their parents, than 6- to 15-year-olds. When depressive problems were assessed in the spring and summer, there were no significant age category differences. However, the age × season-of-assessment interaction was only significant on one of four outcomes, parent-rated depressive problem severity. This interaction was not observed when depressive problems were self-rated on the YSR or when examining the combined borderline and clinical levels of depressive problems on either the CBCL or YSR. There was no gender × season-of-assessment interaction, and contrary to our expectation, older age boys and girls did not differ on depressive problem severity or prevalence in the fall and winter as compared to the spring and summer on the CBCL or the YSR (Hypothesis 3 was not supported). A different pattern of findings on the CBCL versus the YSR is not surprising as correlations between the parent-rated withdrawn/ depressed scale and the child-rated withdrawn/depressed scale were low to moderate. This is consistent with previous findings that parent–child agreement is lower for affective problems such as depression than for conduct problems (Edelbrock et al., 1986) and, specifically, that correlations between child and informant reports are typically in the range of r = 0.20–0.27 (Achenbach et al., 1987). It is important to note that parent and child reports represent different perspectives on child behavior, each of which can provide valid and useful information. In a large epidemiological study of 6608 adults across four European countries, season-of-testing was not a moderator of Beck Depression Inventory (BDI) scores (Michalak et al., 2004), which is consistent with the lack of an overall season-of-assessment main effect in this study. Despite the use of well-validated measures such as the BDI, CBCL, and YSR for measuring depressive problems, robust seasonof-testing differences are not generally evident in large epidemiological studies. Items on the BDI, CBCL, and YSR measure affective problems (e.g. sad mood, lack of interest in previously enjoyable activities, lack of energy), as opposed to atypical depressive symptoms such as hypersomnia and increased appetite that are common in SAD.
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Given that affective problems of depression are necessary for SAD diagnoses, fall/winter increases in SAD symptoms should be captured by measures such as the CBCL and YSR despite the absence of some of the more atypical problems. Furthermore, our SAD scale, although not empirically derived, included several atypical problems (e.g., “overeats,” “overtired,” and “sleeps more”) and revealed identical findings to the CBCL withdrawn/depressed syndrome scale. It is, therefore, unlikely that our failure to detect seasonal differences reflected a lack of atypical problems in the withdrawn/depressed scale. Despite the wide range of latitudes represented, latitude did not significantly moderate the relation between season-of-assessment and depressive problem severity and prevalence on either the CBCL or the YSR (Hypothesis 4 was not supported). In U.S. adults, SPAQ-derived SAD prevalence rates generally increase with latitude (Mersch et al., 1999; Rosen et al., 1990). In the two prior pediatric studies, retrospective estimates of winter SAD diagnosis also increased with latitude in the U.S. (Carskadon and Acebo, 1993) and Finland (Sourander et al., 1999). However, epidemiological studies using DSM-III and DSM-IV criteria for SAD diagnosis did not find latitude effects on SAD prevalence (Blazer et al., 1998; Levitt and Boyle, 2002). Therefore, the lack of a latitude effect in this study is not surprising. Strengths of our study include a relatively large sample that was rigorously selected to be representative of U.S ethnicity, SES, and geographic location. In addition, the CBCL and YSR are empirically derived, well-validated instruments that have age- and gender-specific norms. These quantitative and dichotomous measures enabled us to test depressive problems from both dimensional and binary perspectives. There are also several limitations. First, the CBCL and the YSR ask respondents to rate each problem item “now or within the past 6 months.” If followed literally, these instructions would lead respondents to include depressive problems from prior as well as current seasons. Furthermore, the small number of assessments conducted in the summer months did not permit true winter versus summer comparisons. The latter limitation also prevented us from performing month-to-month comparisons. As mentioned previously, the withdrawn/depressed scale is not empirically derived or validated as a measure of SAD. In addition, our study used a cross-0sectional design. Future research should examine seasonal trends in depression using prospective longitudinal designs, whereby the same children are assessed repeatedly over the seasons. Our one significant finding of an age-by-season-of-assessment interaction, which, in post-hoc analyses, revealed a fall/winter seasonal exacerbation of depressive problems at ages 16–18 has potential clinical implications. Specifically, parents may begin to detect greater fall/winter than spring/summer depressive problems when their children enter middle adolescence. Seasonality, or the tendency to vary in mood and behavior across the seasons, and SAD have been widely reported in adult populations (Magnusson, 2000, 2005) and in previous pediatric studies (Carskadon and Acebo, 1993; Swedo et al., 1995). However, overall seasonal-of-testing differences in depressive symptoms in pediatric populations, especially with younger ages, may not be detectible.
References Aiken, L.S., West, S.G., 1991. Multiple Regression: Testing and Interpreting Interactions. Sage, Newbury Park, CA. Achenbach, T.M., McConaughy, S.H., Howell, C.T., 1987. Child/adolescent behavioral and emotional problems: implications of cross-informant correlations for situational specificity. Psychological Bulletin 101, 213–232. Achenbach, T.M., Rescorla, L.A., 2001. Manual for the ASEBA School-Age Forms & Profiles. University of Vermont, Research Center for Children, Youth, & Families, Burlington, VT. American Psychiatric Association, 2000. Diagnostic and Statistical Manual of Mental Disorders (4th ed.- text revision). APA, Washington, DC. Blazer, D.G., Kessler, R.C., Swartz, M.S., 1998. Epidemiology of recurrent major and minor depression with a seasonal pattern: the National Comorbidity Survey. British Journal of Psychiatry 172, 164–167. Carskadon, M.A., Acebo, C., 1993. Parental reports of seasonal mood and behavior changes in children. Journal of the American Academy of Child and Adolescent Psychiatry 32, 264–269. Doganay, Z., Sunter, T.A., Guz, H., Ozkan, A., Altintop, L., Kati, C., Colak, E., Aygun, D., Guven, H., 2003. Climatic and diurnal variation in suicide attempts in the ED. American Journal of Emergency Medicine 21, 271–275. Edelbrock, C., Costello, A.J., Dulcan, M.K., Conover, N.C., Kala, R., 1986. Parent–child agreement on child psychiatric symptoms assessed via structured interview. Journal of Child Psychological Psychiatry 27, 181–190. Hankin, B.L., Abramson, L.Y., Moffitt, T.E., Silva, P.A., McGee, R., Angell, K.E., 1998. Development of depression from preadolescence to young adulthood: emerging gender differences in a 10-year longitudinal study. Journal of Abnormal Psychology 107, 128–140. Hollingshead, A.B., 1975. Four factor index of social status. Unpublished manuscript. Yale University, Department of Sociology. Kasper, S., Wehr, T.A., Bartko, J.J., Gaist, P.A., Rosenthal, N.E., 1989. Epidemiological findings of seasonal changes in mood and behavior. A telephone survey of Montgomery County, Maryland. Archives of General Psychiatry 46, 823–833. Lee, H.C., Lin, H.C., Tsai, S.Y., Chen, C.C., Huang, C.C., 2006. Suicide rates and the association with climate: a population-based study. Journal of Affective Disorders 92, 221–226. Levitt, A.J., Boyle, M.H., 2002. The impact of latitude on the prevalence of seasonal depression. Canadian Journal of Psychiatry 47, 361–367. Magnusson, A., 1996. Validation of the Seasonal Pattern Assessment Questionnaire (SPAQ). Journal of Affective Disorders 40, 121–129. Magnusson, A., 2000. An overview of epidemiological studies on seasonal affective disorder. Acta Psychiatrica Scandinavica 101, 176–184. Magnusson, A., 2005. The diagnosis, symptomatology, and epidemiology of Seasonal Affective Disorder. CNS Spectrums 10, 625–634. Mersch, P.P.A., Middendorp, H.M., Bouhuys, A.L., Beersma, D.G.M., van den Hoofdakker, R.H., 1999. Seasonal affective disorder and latitude: a review of the literature. Journal of Affective Disorders 53, 35–48. Michalak, E.E., Murray, G., Wilkinson, C., Dowrick, C., Lasa, L., Lehtinen, V., Dalgard, O.D., Ayuso-Mateos, J.L., Vazquez-Barquero, J.L., Casey, P., 2004. Estimating depression prevalence from the Beck Depression Inventory: is season of administration a moderator? Psychiatry Research 129, 99–106. Murray, G., 2003. The Seasonal Pattern Assessment Questionnaire as a measure of mood seasonality: a prospective validation study. Psychiatry Research 120, 53–59. Ott, R.L., 1993. An introduction to Statistical Methods and Data Analysis (4th ed.). Duxbury Press, Belmont, CA. Rosen, L.N., Targum, S.D., Terman, M., Bryant, M.J., Hoffman, H., Kasper, S.F., Hamovit, J.R., Docherty, J.P., Welch, B., Rosenthal, N.E., 1990. Prevalence of seasonal affective disorder at four latitudes. Psychiatry Research 31, 131–144. Rosenthal, N.E., Bradt, G.H., Wehr, T.A., 1987, Seasonal Pattern Assessment Questionnaire. National Institute of Mental Health, Bethesda, MD. Sourander, A., Koskelainem, M., Helenius, H., 1999. Mood, latitude, and seasonality among adolescents. Journal of the American Academy of Child and Adolescent Psychiatry 38, 1271–1276. Swedo, S.E., Pleeter, J.D., Richter, D.M., Hoffman, C.L., Allen, A.J., Hamburger, S.D., Turner, E.H., Yamada, E.M., Rosenthal, N.E., 1995. Rates of sensational affective disorder in children and adolescents. American Journal of Psychiatry 152, 1016–1019. Tonetti, L., Barbato, G., Fabbri, M., Adan, A., Natale, V., 2007. Mood seasonality: a crosssectional study of subjects aged between 10 and 25 years. Journal of Affective Disorders 97, 155–160.
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Psychiatry Research j o u r n a l h o m e p a g e : w w w. e l s ev i e r. c o m / l o c a t e / p s yc h r e s
Seasonal trends in depressive problems among United States children and adolescents: A representative population survey Yael I. Nillni a, Kelly J. Rohan a,⁎, David Rettew b, Thomas M. Achenbach b a b
Department of Psychology, University of Vermont, John Dewey Hall, 2 Colchester Ave., Burlington, VT, USA Department of Psychiatry, University of Vermont, 1 South Prospect St., Burlington, VT, USA
a r t i c l e
i n f o
Article history: Received 30 April 2008 Received in revised form 10 July 2008 Accepted 22 July 2008 Keywords: Seasonal affective disorder Depression Epidemiology
a b s t r a c t This study examined season-of-assessment differences in parent and child reports of depressive problems on well-validated instruments in 2009 U.S. children and adolescents, aged 6 to 18 years, from a nationally representative population survey. A parent completed the Child Behavior Checklist (CBCL) for each participant and 1226 of the 11–18-year-olds completed the Youth Self-Report (YSR). Outcome measures were CBCL and YSR withdrawn/depressed syndrome scale scores and rates of clinically elevated scores. Overall fall/ winter versus spring/summer differences were not found on the CBCL or YSR for depressive problem severity or rates of depressive problems. Age, sex, and latitude were examined as potential moderators of the association between season-of-assessment and the outcomes. Of these, the effect of season-of-assessment on CBCL depressive problem severity depended upon age. Parents of 16–18-year-old adolescents rated depressive problems as significantly more severe in fall and winter than in spring and summer. Parents also rated depressive problems as significantly more severe in 16–18-year-olds than in 6–15-year-olds, but only when assessed in the fall and winter. There were no season-of-assessment differences among 6–15-year-old children and adolescents. The overall lack of season-of-assessment differences and the finding of age as a moderator on only one of four outcomes suggest minimal seasonality effects. © 2008 Elsevier Ireland Ltd. All rights reserved.
1. Introduction The essential feature of Major Depressive Disorder, Recurrent with a Seasonal Pattern is the onset and remission of major depressive episodes at predictable times during the year (American Psychiatric Association, 2000). The most common seasonal pattern is winter seasonal affective disorder (SAD), characterized by depressive episodes that begin in the fall or winter and remit in the spring. Reported prevalence rates for SAD in adults vary considerably, ranging from less than 1% to 9.7% across many countries (Magnusson, 2000, 2005). In contrast to the numerous adult studies, there is considerably less epidemiological research on SAD among children and adolescents. Retrospectively reported prevalence of seasonal onset of depressive symptoms has ranged from 3.3% to 4.2% among American youths (Carskadon and Acebo, 1993; Swedo et al., 1995). Carskadon and Acebo (1993) asked parents of 1860 9- to 12-year-old American children to retrospectively report on their child's seasonal changes in sleeping, eating, irritability, energy, withdrawal, and sadness in the fall (September–November), winter (December–February), and spring (March–May) over the preceding 2 years. A substantial minority (48.5%) of the parents reported at least one recurring symptom in the winter, and 4.2% reported “seems
⁎ Corresponding author: Tel.: +1 802 656 0798; fax: +1 802 656 8783. E-mail address: [email protected] (K.J. Rohan). 0165-1781/$ – see front matter © 2008 Elsevier Ireland Ltd. All rights reserved. doi:10.1016/j.psychres.2008.07.011
sad” plus two other winter symptoms, suggesting that at least subclinical forms of SAD (i.e., the “winter blues”) may be relatively common. In a suburban Maryland sample of 1835 9- to 19-year-olds, 3.3% met criteria for SAD when they completed a modified version of the Seasonal Pattern Assessment Questionnaire (SPAQ; Rosenthal et al., 1987) in late September and early October (Swedo et al., 1995). In contrast, population surveys of Washington, D.C. metro area adults found SPAQprevalence of SAD ranging from 4.3% to 6.3% (Kasper et al., 1989; Rosen et al.,1990). An epidemiological survey of over 1400 Finnish seventh and ninth graders found that 60% to 90% reported seasonal variations in mood and behavior on a modified version of the SPAQ completed during the last week of March (Sourander et al., 1999). A recent study of 1709 Italian children and adolescents who ranged in age from 10 to 17 years found an 8.6% SPAQ-assessed prevalence of SAD (Tonetti et al., 2007). In the Swedo et al. (1995), Sourander et al. (1999), and Tonetti et al. (2007) studies, the SPAQ was modified to include pediatric symptoms of SAD such as poor school performance, conduct problems, and irritability. In conclusion, limited data suggest that fall/winter depression may exist in children and adolescents at rates slightly lower than those reported for adults. As a limitation, most findings were obtained with a modified version of the SPAQ, which, though valuable as a screening tool, may lack specificity and sensitivity (Magnusson, 1996). SPAQderived criteria have been shown to overestimate the prevalence of SAD compared with a diagnostic interview based on DSM-IV criteria (Levitt and Boyle, 2002). The National Comorbidity Study reported prevalence
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rates of 0.4% for major depression with a seasonal pattern and 1% for minor depression with a seasonal pattern, based on DSM-III and DSM-IV criteria in a random US community sample of 8098 adolescents and adults, aged 15–54 (Blazer et al., 1998). Furthermore, the SPAQ is a retrospective survey that was not designed or standardized for pediatric samples. Assessment during either spring or fall poses the potential problem of poor recall for actual symptoms experienced during prior winter seasons. In support of this possibility, SPAQ global seasonality scores and responses to the SPAQ question of whether or not seasonal changes constitute a problem (both of which are considered in the SPAQ diagnosis of SAD) are not associated with prospectively measured summer–winter differences in mood (Murray, 2003). Previous research is also limited by the restricted age range of the samples studied. To our knowledge, there are no published data on SAD in children under the age of 9. Importantly, none of the previous reports on SAD among U.S. children and adolescents used a nationally representative sample, and prior studies included either child or parent reports, but not both. Thus, research on representative samples assessed with well-validated pediatric instruments from the perspective of both child and parent is needed to shed light on possible seasonal variations in mood among children and adolescents. Increased understanding is also needed regarding potential moderators of seasonal trends. Several studies have shown a significant association between latitude and SAD prevalence among adults in the United States, whereby the prevalence of SAD is higher at northern than at southern latitudes (Rosen et al., 1990; Mersch et al., 1999; Magnusson, 2005). However, these studies are limited by their exclusive use of the SPAQ. The National Comorbidity Survey did not find a latitude effect when using DSM-III and DSM-IV criteria for SAD diagnosis (Blazer et al., 1998). Furthermore, the prevalence of DSM-IV SAD diagnoses did not differ by latitude among 1605 participants throughout Canada (41.5°N to 49.5°N; Levitt and Boyle, 2002). Only two studies have examined the relation between latitude and SAD among children and adolescents. Consistent with the SPAQ-based adult literature, both studies reported greater seasonality at higher latitudes (Carskadon and Acebo, 1993; Sourander et al., 1999), but one study found this only for girls (Sourander et al., 1999). The Swedo et al. (1995) survey found that age correlated positively with SAD prevalence. For females only, participants who were postpubescent (determined by whether they had begun menarche) had a higher prevalence of SAD (4.5%) than females who were pre-pubescent (1.7%). Similarly, the Tonetti et al. (2007) survey found that, regardless of gender, seasonality scores increased with age; however, beginning at age 14, females displayed higher seasonality scores than males (Tonetti et al., 2007). This parallels findings of higher rates of non-seasonal depression for females than males after puberty (Hankin et al., 1998). Using a national sample of 6- to 18-year-olds selected to be representative of U.S. demographics on ethnicity, socioeconomic status, and geographic location, we had the following aims: (1) to compare depressive problem severity and clinical levels of depressive problems among children and adolescents assessed in the fall and winter (September–February) versus the spring and summer (March–August), and (2) to test whether age, gender, and latitude would moderate associations between season-of-assessment and depressive problem severity and prevalence. We hypothesized that (1) depressive problem severity and the prevalence of clinical levels of depressive problems would be greater in the fall and winter versus the spring and summer. Based on prior reports that seasonality of mood correlated positively with age (Swedo et al., 1995; Tonetti et al., 2007), we hypothesized that (2) older participants would have greater depressive problem severity and prevalence in the fall and winter than younger participants. In addition, based on prior studies (Swedo et al., 1995; Tonetti et al., 2007), we hypothesized that (3) the main effects of age and gender would interact, whereby fall/winter depressive problem severity and prevalence would be higher for females than males but only among older adolescents. Lastly, based on two preliminary reports (Carskadon and
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Acebo, 1993; Sourander et al., 1999), we hypothesized that (4) fall/ winter depressive problems would be more severe and prevalent for individuals in northern than in southern latitudes. 2. Methods 2.1. Participants and procedure Participants were assessed in a national survey conducted from February 1999 through January 2000 (Achenbach and Rescorla, 2001), using a national sampling frame maintained by Temple University's Institute for Survey Research (ISR) that insured a nationally representative sample across ethnicity, socioeconomic status, and geographic location. Approximately 150 households in each of 100 Primary Sampling Units (PSUs; i.e., areas that are collectively representative of the 48 contiguous United States) were visited in order to determine eligibility for the study. Eligible residents for the current study were at least 6 years old and had no major physical problems or mental retardation. They were selected by stratified randomized procedures that yielded similar proportions of each gender at each age. One parent of each eligible, randomly chosen 6- to 18-year-old participated. During an in-home interview, parents completed the Child Behavior Checklist (CBCL) and answered demographic questions. Youths aged 11 to 18 years were asked to complete the Youth Self-Report (YSR). Of the 2181 eligible 6- to 18-year-olds, parents of 2009 (92.1%) completed the CBCLs that were used in this study. The sample (N = 2009) included participants from 40 states and the District of Columbia. Table 1 summarizes demographics. Of the 1285 eligible 11- to 18-year-olds, 1226 (95.4%) completed the YSR and were included in analyses of youth-rated depressive problems. 2.2. Measures The Child Behavior Checklist (CBCL; Achenbach and Rescorla, 2001) is a widely used instrument that assesses a broad range of competencies and problems. The reliability and validity of the CBCL are well established (Achenbach and Rescorla, 2001). It includes 120 specific problem items and 20 competence items in areas such as social and school functioning. The parent rates problem items over the past 6 months as 0 = “not true (as far as you know),” 1 = “somewhat or sometimes true,” and 2 = “very true or often true.” These problem items are scored on statistically derived syndrome scales and on DSM-oriented scales. Because the CBCL does not have a specific SAD scale, we examined the items of several scales to identify the scale with the best conceptual fit to SAD. The DSM Affective Problems Scale, the anxious/depressed syndrome scale, and the withdrawn/depressed syndrome scale were all considered. We also constructed our own SAD scale using items that tapped the following problems: “overeating,” “sleeps more,” “feels worthless,” “enjoys little,” “would rather be alone,” “lacks energy,” “sad,” “withdrawn,” “guilty,” “overtired,” and “irritable.” The 10-item Affective Problems scale, although consistent with DSM-IV criteria for Major Depression, contains two suicide items (i.e., harms self and talks about suicide) that might be confounded with the widely replicated spring peak in suicides (Doganay et al., 2003; Lee et al., 2006). The anxious/depressed scale contains many anxiety symptoms not common in SAD. We, therefore, focused on the new SAD scale and on the withdrawn/depressed syndrome scale, which, of the empirically derived scales, includes items most representative of SAD symptoms (“enjoys little,” “would rather be alone,” “won’t talk,” “secretive,” “shy/timid,” “lacks energy,” “sad,” and “withdrawn”). The withdrawn/depressed scale is scored by summing the ratings on its constituent items. In addition, there are dichotomous cutoff points reflecting “clinical” and “borderline clinical” levels of problems based on the distribution of scale scores. Depressive problem severity was measured by continuous raw scores on the withdrawn/ depressed scale, which can range from 0 to 16. Continuous raw scores on the new SAD scale were used as a secondary measure of depressive problem severity. Clinical levels of depressive problems were defined as withdrawn/depressed scores in the combined borderline and clinical ranges, i.e., ≥ 93rd percentile for the child's age and gender, based on the CBCL normative samples. We did not examine clinically elevated levels of scores on the SAD scale because there is no empirically defined clinical cut point.
Table 1 Demographic information for 6- to 18-year-olds with parent ratings on the Child Behavior Checklist (N = 2009). Age, M (S.D.) Gender, No. (%) Male Female Ethnicity, No. (%) White African American Asian American Indian/Alaska Native Hispanic/Latino Pacific Islander Socioeconomic Status, M (S.D.)a
12.0 (0.5) 1073 (52.8%) 956 (47.1%) 1241 (61.1%) 387 (19.1%) 165 (8.1%) 18 (0.9%) 179 (8.8%) 39 (1.9%) 5.5 (1.9)
a Based on Hollingshead's (1975) 9-step scale for the parent having the higher status occupation.
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The Youth Self-Report (YSR; Achenbach and Rescorla, 2001) is a companion instrument of the CBCL designed to be completed by youths aged 11–18. The reliability and validity of the YSR are well established (Achenbach and Rescorla, 2001). Measures included YSR withdrawn/depressed syndrome scale raw scores and clinical status (≥93rd percentile based on norms). Continuous raw scores on the newly created YSR SAD scale represented a secondary measure of depressive problem severity. Latitude of the child's residence was assigned to one of five categories ≥45°N, 40°– 44°N, 35°–39°N, 30°–34°N, and 25°–29°N. Socioeconomic status (SES) was scored on Hollingshead's (1975, unpublished manuscript) 9-step scale for the parent having the higher status occupation. 2.3. Data analysis SPSS 12.0 was used for all analyses with alpha b 0.05, 2-tailed. The outcome measures were depressive problem severity and point-prevalence for elevated depressive problems scores in the combined clinical and borderline clinical range. A one-way analysis of variance tested differences in withdrawn/depressed scores on the CBCL and YSR between questionnaires completed in the fall/winter versus those completed in the spring/summer. This dichotomous categorization of season was chosen to avoid the very unequal sample sizes in a comparison of all four seasons (fall: Sep.–Nov. = 708, winter: Dec.–Feb.= 272, spring: March–May= 1009, and summer: Jun.–Aug. =20), which would have violated the ANOVA assumption that sample sizes should be nearly equal (Ott, 1993). When we combined fall with winter, the sample size was 980 for the CBCL and 612 for the YSR, while for spring combined with summer, the sample size was 1029 for the CBCL and 614 for the YSR. The ANOVA was repeated using the new SAD scale on both measures. The proportions of children and adolescents meeting borderline or clinical levels of depressive problems on the CBCL and YSR withdrawn/depressed scales within fall/winter and spring/summer were compared using Chi-square. The second set of analyses tested whether age, gender, and/or latitude moderated the relation between season-of-assessment and depressive problem severity. To examine age, gender, their combined influence, and latitude an ANCOVA tested the main effects of age, gender, season, and latitude as well as the 2-way and 3-way interactions between these main effects, while controlling for the main effects of ethnicity and SES as covariates. ANCOVAs were applied to the CBCL and YSR withdrawn/depressed scale scores and to the new SAD scale on both measures. A hierarchical logistic regression tested whether age, gender, latitude and the interaction of age and gender moderate the relation between season-of-assessment and clinical levels of depressive problems. Age, gender, SES, ethnicity, and latitude were entered in step 1; season-of-assessment (fall/winter versus spring/summer) was entered in step 2; the interaction term for age × gender was entered in step 3; and the interaction terms for gender × season, age × season, season × age × gender, and season× latitude were entered in step 4. The above analyses were repeated using the YSR withdrawn/depressed dichotomous outcome variable of borderline clinical or higher levels of depressive problems as the dependent measure. In order to reduce multicollinearity and maximize interpretability, the predictors used in each interaction were mean centered prior to running the analysis using the procedures outlined by Aiken and West (1991).
3. Results 3.1. Correlations between child and parent reports Tables 2 and 3 summarize the correlations between child and parent reports. All combinations of parent scores versus child yielded low to moderate correlations. This is consistent with previous findings on correlations between parent and self-reports (Achenbach et al., 1987). 3.2. Seasonal trends in depressive problem severity and prevalence— Hypothesis 1 Because results on the SAD scale replicated those on the empirically validated depressed/withdrawn syndrome scales, we present results Table 2 Pearson correlations between parent-completed CBCL withdrawn/depressed raw score and child-completed YSR withdrawn/depressed raw score.
All parents Mother Father Other guardian ⁎⁎P b 0.01 (2-tailed). ⁎P b 0.05 (2-tailed).
All children
Female child
Male child
r (n)
r (n)
r (n)
0.36 (1235)⁎⁎ 0.36 (887)⁎⁎ 0.33 (261)⁎⁎ 0.45 (87)⁎⁎
0.42 (585)⁎⁎ 0.44 (428)⁎⁎ 0.31 (113)⁎⁎ 0.52 (44)⁎⁎
0.31 (650)⁎⁎ 0.30 (459)⁎⁎ 0.35 (148)⁎⁎ 0.32 (43)⁎
Table 3 Pearson correlations between clinically elevated scores of the withdrawn/depressed scale on the parent-completed CBCL and child-completed YSR.
All parents Mother Father Other guardian
All children
Female child
Male child
r (n)
r (n)
r (n)
0.24 (1235)⁎⁎ 0.26 (887)⁎⁎ 0.19 (261)⁎⁎
0.30 (585)⁎⁎ 0.33 (428)⁎ 0.18 (113) 0.30 (44)
0.20 (650)⁎⁎ 0.21 (459)⁎⁎ 0.20 (148)⁎ 0.10 (43)
0.20 (87)
⁎⁎P b 0.01 (2-tailed). ⁎P b 0.05 (2-tailed).
only for the withdrawn/depressed scale. The one-way ANOVAs and Chi squares yielded no significant fall/winter versus spring/summer differences in depressive problem severity [F1, 2007 = 0.92; P = 0.34, η2 = 0.000] or prevalence [χ21 = 1.089; P = 0.297, Φ = 0.023] on the CBCL withdrawn/depressed scale or on the YSR withdrawn/depressed scale [F1, 1225 = 1.46; P = 0.23, η2 = 0.001 and χ21 = 0.622; P = 0.430, Φ = 0.023]. Table 4 presents fall/winter and spring/summer raw scores and rates of clinically elevated scores on the CBCL and YSR. 3.3. Age and sex as moderators of the relation between season-ofassessment and depressive problem severity and prevalence—Hypotheses 2 and 3 In both the ANCOVA and logistic hierarchical regression analyses, the gender × season-of-assessment interaction was not significant for either the CBCL or YSR. The age × season-of-assessment interaction term was significant for depressive problem severity on the CBCL, F1, 1898 = 5.2; P = 0.023, η2 = 0.003 in the ANCOVA, suggesting that the effect of age depends upon season-of-assessment, while controlling for gender, ethnicity, SES, latitude, and the main effects of age and season. In order to explore this interaction further, we performed post-hoc ANCOVAs to test the effect of season at each age on depressive symptom severity, while controlling for gender, ethnicity, SES, and latitude. The adjusted means of depressive problem severity at each age and season are shown in Fig. 1. Although there were no significant season-ofassessment differences when each age was examined separately, we observed a consistent pattern of fall/winter elevation of depressive problem severity over spring/summer depressive problems beginning at age 16. We re-ran the ANCOVA, using age categories (6–15 and 16–18) in order to compare these two age groups. The age category× season-ofassessment interaction term was significant for depressive problem severity on the CBCL, F1, 1898 = 8.4; P = 0.004, η2 = 0.004 (Fig. 2). Posthoc analyses revealed that depressive problem severity scores were significantly higher in the fall/winter than in the spring/summer among older adolescents, aged 16–18, F1, 383 = 4.6; P = 0.032, η2 = 0.012, but did not differ across season-of-assessment among younger children and adolescents, aged 6–15, F1, 1511 = 2.3; P = 0.132, η2 = 0.001. The effect size corresponding to the season-of-assessment difference among
Table 4 Mean withdrawn/depressed scores and rates of clinically elevated scores in fall/winter and spring/summer seasons of assessment. Season-of-assessment Measure
Fall/winter
Spring/summer
Raw scores, M (S.D.), n CBCL w/d YSR w/d
1.5 (2.2), 980 3.0 (2.6), 612
1.8 (2.2), 1029 3.2 (2.6), 614
Rates of clinically elevated scores, No. (%) CBCL w/d 86 (9.6%) YSR w/d 50 (8.2%)
100 (9.0%) 58 (9.5%)
CBCL w/d = Child Behavior Checklist withdrawn/depressed syndrome scale, YSR w/ d = Youth Self-Report withdrawn/depressed syndrome scale. Rate of clinically elevated scores is defined as scores ≥ 93rd percentile based on CBCL and YSR normative samples.
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3.4. Latitude as a moderator of the relation between season-of-assessment and depressive problem severity and prevalence—Hypothesis 4 The latitude × season-of-assessment interaction was not significant in either the ANCOVA analysis or the logistic regressions, suggesting that latitude did not significantly moderate the relation between season-of-assessment and depressive problem severity and prevalence on either the CBCL or the YSR. 4. Discussion
Fig. 1. Mean CBCL withdrawn/depressed syndrome scale scores in fall/winter versus spring/summer for participants aged 6–18, adjusted for gender, ethnicity, SES, and latitude.
16 to 18-year-olds was d = 0.15. Age category differences were then examined separately for each season. Parents of adolescents aged 16–18 reported significantly more depressive problems than parents of children and adolescents aged 6–15 when assessed in the fall and winter, F1, 925 = 26.98; P = 0.000, η2 = 0.028. The effect size corresponding to the age category group difference (6–15 versus 16–18) within the fall/winter season-of-assessment was d = 0.24. There were no differences between these two age groups on CBCL depressive problem severity when assessed in the spring and summer, F1, 969 = 1.5; P = 0.227, η2 = 0.002. The age × season-of-assessment interaction was not significant in the ANCOVA for YSR scores or in the hierarchical logistic regressions of combined borderline and clinical levels of depressive problems according to the CBCL and YSR. The 3-way age × gender × season interaction was not significant on the CBCL or YSR in the ANCOVA analysis using raw scores or in the logistic regressions using borderline or clinical status. Given that the age × season-of-assessment interaction was significant for CBCL scores, but not for YSR scores, we examined whether differences in parent–child agreement might explain this discrepancy. As only 11–18-year-olds completed the YSR, we examined correlations between parent reports on the CBCL and child reports on the YSR separately for ages 11–15 versus 16–18. Correlations between parent and child reports of depressive problem severity did not differ by age subsample (r = 0.34 for 11–15 versus r = 0.38 for 16–18; z = −0.75, P = 0.45). Therefore, it does not appear likely that a difference in parent–child agreement explains these discrepant findings.
Fig. 2. Mean CBCL withdrawn/depressed syndrome scale scores in fall/winter versus spring/summer for participants aged 6–14 and 15–18, adjusted for gender, ethnicity, SES, and latitude.
To our knowledge, this is the first study to examine seasonal trends in depressive problem severity and prevalence in a sample representative of U.S. children and adolescents across ethnicity, SES, and geographic location. It is also the first to use a validated pediatric measure of depressive problem severity and borderline or clinical status of these depressive problems to test season-of-assessment differences as well as gender, age, and latitude as potential moderators. This study also included the widest age span to date, ages 6 to 18 years. In the sample as a whole, depressive problem severity and prevalence did not differ according to whether problems were reported in the fall and winter versus in the spring and summer (Hypothesis 1 was not supported). However, age was found to significantly moderate the relation between season-of-assessment and depressive problem severity on the CBCL (Hypothesis 2 was supported on one of four outcome measures). Specifically, parents of older adolescents (aged 16–18) rated their adolescents' depressive problems as significantly more severe in the fall or winter than in the spring or summer. Younger children and adolescents (aged 6–15) showed no significant season-of-assessment differences in depressive problem severity. When assessed in the fall and winter, 16- to 18-year-olds had significantly greater depressive problems, as rated by their parents, than 6- to 15-year-olds. When depressive problems were assessed in the spring and summer, there were no significant age category differences. However, the age × season-of-assessment interaction was only significant on one of four outcomes, parent-rated depressive problem severity. This interaction was not observed when depressive problems were self-rated on the YSR or when examining the combined borderline and clinical levels of depressive problems on either the CBCL or YSR. There was no gender × season-of-assessment interaction, and contrary to our expectation, older age boys and girls did not differ on depressive problem severity or prevalence in the fall and winter as compared to the spring and summer on the CBCL or the YSR (Hypothesis 3 was not supported). A different pattern of findings on the CBCL versus the YSR is not surprising as correlations between the parent-rated withdrawn/ depressed scale and the child-rated withdrawn/depressed scale were low to moderate. This is consistent with previous findings that parent–child agreement is lower for affective problems such as depression than for conduct problems (Edelbrock et al., 1986) and, specifically, that correlations between child and informant reports are typically in the range of r = 0.20–0.27 (Achenbach et al., 1987). It is important to note that parent and child reports represent different perspectives on child behavior, each of which can provide valid and useful information. In a large epidemiological study of 6608 adults across four European countries, season-of-testing was not a moderator of Beck Depression Inventory (BDI) scores (Michalak et al., 2004), which is consistent with the lack of an overall season-of-assessment main effect in this study. Despite the use of well-validated measures such as the BDI, CBCL, and YSR for measuring depressive problems, robust seasonof-testing differences are not generally evident in large epidemiological studies. Items on the BDI, CBCL, and YSR measure affective problems (e.g. sad mood, lack of interest in previously enjoyable activities, lack of energy), as opposed to atypical depressive symptoms such as hypersomnia and increased appetite that are common in SAD.
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Given that affective problems of depression are necessary for SAD diagnoses, fall/winter increases in SAD symptoms should be captured by measures such as the CBCL and YSR despite the absence of some of the more atypical problems. Furthermore, our SAD scale, although not empirically derived, included several atypical problems (e.g., “overeats,” “overtired,” and “sleeps more”) and revealed identical findings to the CBCL withdrawn/depressed syndrome scale. It is, therefore, unlikely that our failure to detect seasonal differences reflected a lack of atypical problems in the withdrawn/depressed scale. Despite the wide range of latitudes represented, latitude did not significantly moderate the relation between season-of-assessment and depressive problem severity and prevalence on either the CBCL or the YSR (Hypothesis 4 was not supported). In U.S. adults, SPAQ-derived SAD prevalence rates generally increase with latitude (Mersch et al., 1999; Rosen et al., 1990). In the two prior pediatric studies, retrospective estimates of winter SAD diagnosis also increased with latitude in the U.S. (Carskadon and Acebo, 1993) and Finland (Sourander et al., 1999). However, epidemiological studies using DSM-III and DSM-IV criteria for SAD diagnosis did not find latitude effects on SAD prevalence (Blazer et al., 1998; Levitt and Boyle, 2002). Therefore, the lack of a latitude effect in this study is not surprising. Strengths of our study include a relatively large sample that was rigorously selected to be representative of U.S ethnicity, SES, and geographic location. In addition, the CBCL and YSR are empirically derived, well-validated instruments that have age- and gender-specific norms. These quantitative and dichotomous measures enabled us to test depressive problems from both dimensional and binary perspectives. There are also several limitations. First, the CBCL and the YSR ask respondents to rate each problem item “now or within the past 6 months.” If followed literally, these instructions would lead respondents to include depressive problems from prior as well as current seasons. Furthermore, the small number of assessments conducted in the summer months did not permit true winter versus summer comparisons. The latter limitation also prevented us from performing month-to-month comparisons. As mentioned previously, the withdrawn/depressed scale is not empirically derived or validated as a measure of SAD. In addition, our study used a cross-0sectional design. Future research should examine seasonal trends in depression using prospective longitudinal designs, whereby the same children are assessed repeatedly over the seasons. Our one significant finding of an age-by-season-of-assessment interaction, which, in post-hoc analyses, revealed a fall/winter seasonal exacerbation of depressive problems at ages 16–18 has potential clinical implications. Specifically, parents may begin to detect greater fall/winter than spring/summer depressive problems when their children enter middle adolescence. Seasonality, or the tendency to vary in mood and behavior across the seasons, and SAD have been widely reported in adult populations (Magnusson, 2000, 2005) and in previous pediatric studies (Carskadon and Acebo, 1993; Swedo et al., 1995). However, overall seasonal-of-testing differences in depressive symptoms in pediatric populations, especially with younger ages, may not be detectible.
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